Intelligent mobile first field sales productivity tool with the modules that fit your unique enterprise demands, streamlining field sales and customer onboarding like never before.

Toolyt

<strong>Toolyt</strong> | 3,698 followers on LinkedIn. Intelligent Personal Assistant for Sales Team | <strong>Toolyt</strong> is an intelligent personal assistant for field officers; which is automated by the data and event-driven workflows (custom &amp; default).

Toolyt | LinkedIn

12 <strong>Toolyt</strong> reviews in Bangalore, India. A free inside look at <strong>company</strong> reviews and salaries posted anonymously by employees.

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Toolyt - Crunchbase Company Profile & Funding

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Toolyt Company Profile: Valuation & Investors | PitchBook

In 2016, he set up <strong>Toolyt</strong>, an enterprise SaaS application based out of Bengaluru. The platform, which is an intelligent (AI-based) personal assistant for field teams (sales team/relationship managers), helps <strong>companies</strong> increase their productivity 10x by automating their daily operations such ...

This AI-based personal assistant automating workflows for sales ...

&quot;Bengaluru, Karnataka based <strong>Toolyt</strong> is a leading mobile CRM for field sales teams, designed to help salespeople in their day-to-day lives by acting as their personal assistant. Their Intelligent Mobile Assistant that let their <strong>companies</strong> Supercharge their Sales Team on Field, Office &amp; Homes.

Toolyt - YourStory

<strong>Toolyt</strong>&#x27;s top competitor is Vymo, led by Yamini Bhat, who is their Co-Founder &amp; CEO. <strong>Toolyt</strong> has 9 followers on Owler. ... is a Private <strong>company</strong>. Nizamudheen Valliyattu is the Founder of <strong>Toolyt</strong> and has an approval rating of 88 from Owler members. <strong>Toolyt</strong>&#x27;s top competitor is Vymo, led by Yamini ...

Toolyt’s Competitors, Revenue, Number of Employees, Funding, ...

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Tool Company

What is our “Why&quot;? To surpass the highest standards for our aerospace and defense customers who protect our warfighters and freedom around the world.

General Tool Company's

A recognized industry leader trusted by the United States government for over 60 years. With an impeccable reputation and dedication to delivering quality, Wright Tool <strong>Company</strong> is a single integrated solutions provider, bringing parts and service together to provide comprehensive solutions to ...

Wright Tool Company

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Design and manufacture of milling products with indexable carbide inserts, indexable diamond inserts, chamfer, boring, step tools and many other special styles and variations to meet your needs

LOVEJOY Tool Company, Inc. - Manufacturer of Standard and Special ...

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Toolyt is mobile first frontline sales enablement platform, which helps in tracking the sales activities of the sales person who are on field on a real time basis

The Ideal Startup Toolstack to Scale Your Growth

reactjs-popup Home page https://react-popup.elazizi.com/ This article is about giving you a simple overview of what you can do with reactjs-popup and how to use it effectively. Today, we are excited to announce reactjs-popup 1.0. R is a simple and very small (3 kb) react popup component, with multiple use cases. we created reactjs-popup to create a color picker for our project a new online image editor. After a while, We decided to make it available for everyone in GitHub and npm repository. eactjs-popup picsrush Why do you need to choose reactjs-popup over all other implementation? Built with react fragment that’s mean no additional wrapper Divs in your code or in the trigger element. 😮 Does not inject HTML outside your app root. 📦 Function as children pattern to take control over your popup anywhere in your code. 💪 Modal, Tooltip, Menu, Toast(coming soon) : All in one component🏋️ Full style customization. 👌 Easy to use. 🚀 All these clocks in at around 3 kB zipped. ⚡️ Animation (coming soon). How can reactjs-popup help you in your next react project? If you need to create a simple modal, tooltip or a nested menu this component is your best choice to start with. but first let get started with the component. Getting Started This package is available in npm repository as reactjs-popup. It will work correctly with all popular bundlers. _reactjs-popup - React Popup Component - Modals,Tooltips and Menus - All in one_github.com yjose/reactjs-popup npm install reactjs-popup --save#using yarnyarn add reactjs-popup -S Now you can import the component and start using it : import React from "react";import Popup from "reactjs-popup";export default () => (  <Popup trigger={<button> Trigger</button>} position="right center">    <div>Popup content here !!</div>  </Popup>); You can also use it with function as children pattern. import React from "react";import Popup from "reactjs-popup";export default () => (  <Popup trigger={<button>Trigger</button>} position="top left">    {close => (      <div>        Content here        <a className="close" onClick={close}>          &times;        </a>      </div>    )}  </Popup>); Complete component API : Reactjs-popup Component API Use Cases 🙌 Tooltip Use Case Modal Use Case Menu Use Case ALL in one demo reactjs-popup demo (Modal,tooltip,Menu) What’s Next For reactjs-popup ? The next version of reactjs-popup will support creating Simple Toast with full customization, But our big deal is to add Animation API to the component so feel free if you have any ideas 💪. Thanks for reading! If you think other people should read this post and use this component, clap for me, tweet and share the post. Remember to follow me on Medium so you can get notified about my future posts. It your turn now to try it !!! Show your support! That’s all, thank you for your attention, please star the to show your support… repo Read more stories https://elazizi.com/

Introducing reactjs-popup 🎉 —React popup, Modals, Tooltips and Menus — All in one

4 Case Studies in UX Audit: Insights and Best Practices for Improving User Experience

How to Implement Multi-Group Bar Chart and Interact With Highlighting by Grouping Dimension

Python Bokeh is one of the best Python packages for data visualization. Today, we are going to see some Python Bokeh Examples. I have also provided the Python Bokeh project source code on GitHub. Learn this easy visualization tool and add it to your Python stack. What is Python Bokeh? Python is a data visualization tool, or we can also say Python Bokeh is used to plot various types of graphs. There are various other graph plotting libraries like matplotlib, but Python Bokeh graphs are dynamic in nature, which means you can interact with the generated graph. See the below examples… Bokeh Installation 💻: Python Bokeh can be easily installed using PIP. You can install the Python Bokeh easily by running the command: pip install bokeh Now everything is ready, let’s go through the examples 🏃‍♂️… 1. LinePlot from bokeh.plotting import figure, show, output_notebook
x = [1, 2, 3, 4, 5]
y = [4, 5, 5, 7, 3]
p = figure(title="{LinePlot Python Bokeh Example")
p.line(x, y, line_width=2)
output_notebook()
show(p) | | Live Preview Source Code 🌿 Contribute 2. Scatter Plot from bokeh.plotting import figure, show, output_notebook
x = [1, 2, 3, 4, 5]
y = [4, 5, 5, 7, 3]
p = figure(title="Scatter Plot Python Bokeh Example by PratikPathak.com")
p.circle(x, y, size=10, color="navy", alpha=0.5)
output_notebook()
show(p) 3. Bar Chart from bokeh.plotting import figure, show, output_notebook
categories = ["A", "B", "C", "D", "E"]
values = [10, 15, 8, 12, 6]
p = figure(x_range=categories, title="Bar Chart Python Bokeh Example by PratikPathak.com")
p.vbar(x=categories, top=values, width=0.9)
output_notebook()
show(p) 4. Histogram from bokeh.plotting import figure, show, output_notebook
import numpy as np
data = np.random.normal(0, 1, 1000)
p = figure(title="Histogram Python Bokeh Example by PratikPathak.com")
p.hist(data, bins=30, color="navy", alpha=0.5)
output_notebook()
show(p) 5. Pie Chart from bokeh.plotting import figure, show, output_notebook
labels = ["A", "B", "C", "D"]
values = [10, 15, 8, 12]
p = figure(title="Pie Chart Python Bokeh Example by PratikPathak.com")
p.wedge(x=0, y=0, radius=0.4, start_angle=0.6, end_angle=2.6, color=["red", "green", "blue", "yellow"], legend_label=labels)
output_notebook()
show(p) | | Live Preview Source Code 🌿 Contribute 6. Time Series Plot from bokeh.plotting import figure, show, output_notebook
from datetime import datetime, timedelta
start = datetime(2023, 1, 1)
end = start + timedelta(days=30)
x = [start + timedelta(days=i) for i in range((end-start).days)]
y = [10, 15, 8, 12, 6, 18, 9, 14, 7, 11, 5, 16, 8, 13, 6]
p = figure(x_axis_type="datetime", title="Time Series Plot Python Bokeh Example by PratikPathak.com")
p.line(x, y, line_width=2)
output_notebook()
show(p) 7. Linked Brushing from bokeh.plotting import figure, show, output_notebook
from bokeh.models import ColumnDataSource
x1 = [1, 2, 3, 4, 5]
y1 = [4, 5, 5, 7, 3]
x2 = [2, 3, 4, 5, 6]
y2 = [2, 4, 6, 8, 4]
source = ColumnDataSource(data=dict(x1=x1, y1=y1, x2=x2, y2=y2))
p1 = figure(title="Scatter Plot 1")
p1.circle('x1', 'y1', source=source)
p2 = figure(title="Scatter Plot 2 Python Bokeh Example by PratikPathak.com")
p2.circle('x2', 'y2', source=source)
output_notebook()
show(p1, p2) 8. Hover Tooltips from bokeh.plotting import figure, show, output_notebook
from bokeh.models import HoverTool
x = [1, 2, 3, 4, 5]
y = [4, 5, 5, 7, 3]
p = figure(title="Hover Tooltips Python Bokeh Example by PratikPathak.com")
p.circle(x, y, size=15, fill_color="navy", line_color="white", alpha=0.5)
hover = HoverTool(tooltips=[("(x,y)", "(@x, @y)")])
p.add_tools(hover)
output_notebook()
show(p) 9. Annotations from bokeh.plotting import figure, show, output_notebook
from bokeh.models import Arrow, VectorRenderer, Label
x = [1, 2, 3, 4, 5]
y = [4, 5, 5, 7, 3]
p = figure(title="Annotations Python Bokeh Example by PratikPathak.com")
p.circle(x, y, size=15, fill_color="navy", line_color="white", alpha=0.5)
arrow = Arrow(x_start=2, y_start=4, x_end=3, y_end=5, line_width=2, line_color="red")
label = Label(x=3, y=6, text="This is a label", render_mode='css', border_line_color='black', border_line_alpha=1.0, background_fill_color='white', background_fill_alpha=0.5)
p.add_layout(arrow)
p.add_layout(label)
output_notebook()
show(p) 10. Custom Glyphs from bokeh.plotting import figure, show, output_notebook
from bokeh.models.glyphs import Asterisk
x = [1, 2, 3, 4, 5]
y = [4, 5, 5, 7, 3]
p = figure(title="Custom Glyphs Python Bokeh Example by PratikPathak.com")
p.add_glyph(x, y, Asterisk(size=20, line_color="red", fill_color="yellow"))
output_notebook()
show(p) | | Live Preview Source Code 🌿 Contribute 11. Gridlines and Axes from bokeh.plotting import figure, show, output_notebook
x = [1, 2, 3, 4, 5]
y = [4, 5, 5, 7, 3]
p = figure(title="Gridlines and Axes Python Bokeh Example by PratikPathak.com", x_range=(0, 6), y_range=(0, 8))
p.grid.grid_line_color = "grey"
p.grid.grid_line_dash = [6, 4]
p.xaxis.axis_label = "X-axis"
p.yaxis.axis_label = "Y-axis"
p.line(x, y, line_width=2)
output_notebook()
show(p) 12. Legend from bokeh.plotting import figure, show, output_notebook
x1 = [1, 2, 3, 4, 5]
y1 = [4, 5, 5, 7, 3]
x2 = [2, 3, 4, 5, 6]
y2 = [2, 4, 6, 8, 4]
p = figure(title="Legend Python Bokeh Example by PratikPathak.com")
p.line(x1, y1, line_width=2, color="red", legend_label="Line 1")
p.line(x2, y2, line_width=2, color="blue", legend_label="Line 2")
p.legend.location = "top_left"
output_notebook()
show(p) 13. Categorical Plots from bokeh.plotting import figure, show, output_notebook
fruits = ["Apples", "Pears", "Nectarines", "Plums", "Grapes", "Strawberries"]
counts = [5, 3, 4, 2, 4, 6]
p = figure(x_range=fruits, title="Categorical Plots Python Bokeh Example by PratikPathak.com")
p.vbar(x=fruits, top=counts, width=0.9)
p.xaxis.axis_label = "Fruit"
p.yaxis.axis_label = "Count"
p.xaxis.axis_label_text_font_size = "12pt"
p.yaxis.axis_label_text_font_size = "12pt"
output_notebook()
show(p) 14. Subplots from bokeh.plotting import figure, show, output_notebook
from bokeh.layouts import gridplot
x1 = [1, 2, 3, 4, 5]
y1 = [4, 5, 5, 7, 3]
x2 = [2, 3, 4, 5, 6]
y2 = [2, 4, 6, 8, 4]
p1 = figure(title="Scatter Plot 1 Python Bokeh Example by PratikPathak.com")
p1.circle(x1, y1, size=10, color="navy", alpha=0.5)
p2 = figure(title="Scatter Plot 2 Python Bokeh Example by PratikPathak.com")
p2.circle(x2, y2, size=10, color="red", alpha=0.5)
grid = gridplot([[p1, p2]], plot_width=400, plot_height=400)
output_notebook()
show(grid) 15. Interactive Plots from bokeh.plotting import figure, show, output_notebook
from bokeh.models import ColumnDataSource, HoverTool, BoxSelectTool
import numpy as np
x = np.random.random(1000)
y = np.random.random(1000)
source = ColumnDataSource(data=dict(x=x, y=y))
p = figure(title="Interactive Plots Python Bokeh Example by PratikPathak.com", tools="hover,box_select")
p.circle('x', 'y', source=source, size=3, color="navy", alpha=0.5)
hover = HoverTool(tooltips=[("(x,y)", "(@x, @y)")])
p.add_tools(hover)
output_notebook()
show(p) | | Live Preview Source Code 🌿 Contribute 16. Linked Panning and Zooming from bokeh.plotting import figure, show, output_notebook
from bokeh.models import Range1d
x1 = [1, 2, 3, 4, 5]
y1 = [4, 5, 5, 7, 3]
x2 = [2, 3, 4, 5, 6]
y2 = [2, 4, 6, 8, 4]
p1 = figure(title="Scatter Plot 1 Python Bokeh Example by PratikPathak.com", x_range=Range1d(0, 6), y_range=Range1d(0, 8))
p1.circle(x1, y1, size=10, color="navy", alpha=0.5)
p2 = figure(title="Scatter Plot 2 Python Bokeh Example by PratikPathak.com", x_range=p1.x_range, y_range=p1.y_range)
p2.circle(x2, y2, size=10, color="red", alpha=0.5)
output_notebook()
show(p1, p2) 17. Linked Axis Ranges from bokeh.plotting import figure, show, output_notebook
from bokeh.models import Range1d
x1 = [1, 2, 3, 4, 5]
y1 = [4, 5, 5, 7, 3]
x2 = [2, 3, 4, 5, 6]
y2 = [2, 4, 6, 8, 4]
p1 = figure(title="Scatter Plot 1", x_range=(0, 6), y_range=(0, 8))
p1.circle(x1, y1, size=10, color="navy", alpha=0.5)
p2 = figure(title="Scatter Plot 2", x_range=p1.x_range, y_range=p1.y_range)
p2.circle(x2, y2, size=10, color="red", alpha=0.5)
output_notebook()
show(p1, p2) 18. DateTime Axis from bokeh.plotting import figure, show, output_notebook
from datetime import datetime, timedelta
start = datetime(2023, 1, 1)
end = start + timedelta(days=30)
x = [start + timedelta(days=i) for i in range((end-start).days)]
y = [10, 15, 8, 12, 6, 18, 9, 14, 7, 11, 5, 16, 8, 13, 6]
p = figure(x_axis_type="datetime", title="Datetime Axis Python Bokeh Example by PratikPathak.com")
p.line(x, y, line_width=2)
output_notebook()
show(p) 19. Heatmap from bokeh.plotting import figure, show, output_notebook
import numpy as np
data = np.random.rand(10, 10)
p = figure(title="Heatmap Python Bokeh Example by PratikPathak.com")
p.image(image=[data], x=0, y=0, dw=10, dh=10, palette="Viridis256")
output_notebook()
show(p) 20. Streamgraph from bokeh.plotting import figure, show, output_notebook
from bokeh.models import ColumnDataSource
import numpy as np
# Generate some sample data
x = np.linspace(0, 10, 100)
y1 = np.cumsum(np.random.randn(100))
y2 = np.cumsum(np.random.randn(100))
y3 = np.cumsum(np.random.randn(100))
y4 = np.cumsum(np.random.randn(100))
y5 = np.cumsum(np.random.randn(100))
source = ColumnDataSource(data=dict(x=x, y1=y1, y2=y2, y3=y3, y4=y4, y5=y5))
p = figure(title="Streamgraph Python Bokeh Example by PratikPathak.com")
p.area(x='x', y1='y1', y2='y2', y3='y3', y4='y4', y5='y5', source=source, line_color=None)
output_notebook()
show(p) | | Live Preview Source Code 🌿 Contribute 21. Polar Plot from bokeh.plotting import figure, show, output_notebook
import numpy as np
r = np.linspace(0.1, 1, 10)
theta = np.linspace(0, 2*np.pi, 10)
p = figure(title="Polar Plot Python Bokeh Example by PratikPathak.com", plot_width=600, plot_height=600, x_range=(-1.2, 1.2), y_range=(-1.2, 1.2), toolbar_location=None)
p.polar(r, theta, color="navy", alpha=0.5, line_width=2)
output_notebook()
show(p) 22. Donut Chart from bokeh.plotting import figure, show, output_notebook
from bokeh.models import ColumnDataSource
labels = ["A", "B", "C", "D"]
values = [10, 15, 8, 12]
source = ColumnDataSource(data=dict(labels=labels, values=values))
p = figure(title="Donut Chart Python Bokeh Example by PratikPathak.com", x_range=labels)
p.wedge(x=0, y=1, radius=0.4, start_angle=0.6, end_angle=2.6, color=["red", "green", "blue", "yellow"], legend_field="labels")
p.wedge(x=0, y=1, inner_radius=0.3, outer_radius=0.4, start_angle=0.6, end_angle=2.6, color="white")
p.axis.visible = False
p.grid.grid_line_color = None
output_notebook()
show(p) 23. Treemap from bokeh.plotting import figure, show, output_notebook
from bokeh.models import TreemapRenderer, ColumnDataSource
import pandas as pd

# Sample data
data = pd.DataFrame({
    'label': ['A', 'B', 'C', 'D', 'E', 'F', 'G', 'H'],
    'parent': ['', 'A', 'A', 'B', 'B', 'C', 'C', 'D'],
    'value': [10, 5, 4, 3, 2, 1, 1, 1]
})

source = ColumnDataSource(data)
p = figure(title="Treemap Python Bokeh Example by PratikPathak.com")
treemap = TreemapRenderer(
    source=source,
    label='label',
    parent='parent',
    value='value',
    color_discrete_sequence=["#e6550d", "#3182bd", "#31a354", "#756bb1", "#636363", "#9e9ac8", "#de2d26", "#fd8d3c"],
)
p.add_layout(treemap)
output_notebook()
show(p) If you get any error, make sure you have installed Python pandas by using the “pip install pandas” command 24. Network Plot from bokeh.plotting import figure, show, output_notebook
from bokeh.models import ColumnDataSource, HoverTool, NodesAndLinkedEdges
import networkx as nx

# Sample data
nodes = ['A', 'B', 'C', 'D', 'E', 'F']
edges = [('A', 'B'), ('A', 'C'), ('B', 'D'), ('B', 'E'), ('C', 'F')]
G = nx.Graph()
G.add_nodes_from(nodes)
G.add_edges_from(edges)

node_positions = nx.spring_layout(G)
node_x = [node_positions[node][0] for node in G.nodes()]
node_y = [node_positions[node][1] for node in G.nodes()]
node_color = ['red', 'green', 'blue', 'yellow', 'purple', 'orange']

source = ColumnDataSource(data=dict(
    x=node_x,
    y=node_y,
    color=node_color,
    node=nodes
))

p = figure(title="Network Plot Python Bokeh Example by PratikPathak.com", x_range=(-1.1, 1.1), y_range=(-1.1, 1.1))
p.add_tools(HoverTool(tooltips=[("Node", "@node")]))
p.circle('x', 'y', size=15, color='color', source=source)

edge_x = []
edge_y = []
for start, end in edges:
    x0, y0 = node_positions[start]
    x1, y1 = node_positions[end]
    edge_x.append(x0)
    edge_x.append(x1)
    edge_x.append(None)
    edge_y.append(y0)
    edge_y.append(y1)
    edge_y.append(None)

p.multi_line(edge_x, edge_y, color="black", alpha=0.5, line_width=1)

output_notebook()
show(p) 25. Sankey Diagram from bokeh.plotting import figure, show, output_notebook
from bokeh.models import Sankey, ColumnDataSource

# Sample data
flows = [
    ('A', 'X', 5),
    ('B', 'X', 3),
    ('A', 'Y', 2),
    ('B', 'Y', 4),
    ('X', 'C', 4),
    ('X', 'D', 3),
    ('Y', 'C', 2),
    ('Y', 'D', 4)
]

source = ColumnDataSource(data=dict(
    source=[flow[0] for flow in flows],
    target=[flow[1] for flow in flows],
    value=[flow[2] for flow in flows]
))

p = figure(plot_width=800, plot_height=400, title="Sankey Diagram Python Bokeh Example by PratikPathak.com")
sankey = Sankey(source=source, label_text_color="white", label_text_font_size="8pt")
p.renderers.append(sankey)

output_notebook()
show(p) | | Live Preview Source Code 🌿 Contribute 26. Chord Diagram from bokeh.plotting import figure, show, output_notebook
from bokeh.models import ColumnDataSource, CategoricalColorMapper
import numpy as np

# Sample data
nodes = ['A', 'B', 'C', 'D', 'E', 'F']
connections = [
    ('A', 'B', 0.5), ('A', 'C', 0.3), ('A', 'D', 0.2),
    ('B', 'C', 0.4), ('B', 'D', 0.3), ('B', 'E', 0.3),
    ('C', 'D', 0.2), ('C', 'E', 0.3), ('C', 'F', 0.5),
    ('D', 'E', 0.2), ('D', 'F', 0.3), ('E', 'F', 0.4)
]

source = ColumnDataSource(data=dict(
    start=np.array([con[0] for con in connections]),
    end=np.array([con[1] for con in connections]),
    value=np.array([con[2] for con in connections])
))

p = figure(title="Chord Diagram Python Bokeh Example by PratikPathak.com", plot_width=800, plot_height=800)
chord = p.chord(
    source=source, 
    start_angle=np.pi / 2,
    direction="clockwise",
    colors=CategoricalColorMapper(factors=nodes, palette="Spectral11")
)

output_notebook()
show(p) How to Contribute? Feel free to open a PR request on our GitHub repo. Steps to contribute: Fork the repo Make changes in the Forked repo and save Open a Pull Request That’s it 😄! 🌿 Contribute Conclusion In this Repo, I have shared 25+ Python Bokeh examples that can help you learn Python Bokeh. Feel free to contribute to our GitHub repo and keep it updated. Also published . here

Getting Started With Python Bokeh: 25+ Data Visualization Examples With Source Code

Emoji Credibility Indicators by HackerNoon are now live on GitHub and Figma!!! Our open-source pixelated emoji pack was designed to communicate context about a story's content on HackerNoon and you can be amongst the first to try them! But before we tell you what you’ll get from this package, here’s a little refresher ⬇️ What are Emoji Credibility Indicators on HackerNoon Stories? Emoji Credibility Indicators provide essential context to the content within every HackerNoon story. Below the author’s profile on the story page, the “Credibility” section appears with a corresponding custom emoji and tooltip to indicate relevant information about the story to the reader. In the example above, you can see that David’s story contains two emoji credibility indicators: HODL, which indicates mentions of one or more cryptos that the author holds, and Associated Companies, which is used when the writer has or had any sort of business relationship with companies mentioned in the story. Learn more about Emoji Credibility Indicators here. Types of Emoji Credibility Indicators We have around 20 emoji credibility indicators for Context and Disclaimers, and Content Types, each with an attributed meaning and instructions on how to use them. So if you have a technological project, and want amazing pixelated emojis to represent/communicate credibility, this repo is for you! Read about all our emoji credibility indicators, what they mean, and how to use them here. Why Adding Context to Content Matters to the Future of Digital Text When lost in a good read, it may feel like there are only words, but the reality is, no text exists in a vacuum. All text has a setting. Too often on social media and the current internet, what surrounds the text is vanity metrics designed to keep you in the newsfeed, designed to re-affirm that what you’re doing is liked/upvoted/not-a-waste-of-time, instead of being designed to provide you with structured indications that define the context of the story. Read our help page fo more context about our emoji credibility indicators. What will you get from this open-source package? Pixelated Emojis, designed on a 24px grid.
Well crafted SVGs
Fully customizable
Ready-to-use for development via GitHub Repo and Figma! Sounds good? Try them out today and tell us about your experience here. Designing HackerNoon's Emoji Credibility Indicators: Get the developer’s perspective here. Emoji Credibility Indicators by HackerNoon are now live on GitHub and Figma!!! Emoji Credibility Indicators by HackerNoon are now live on GitHub and Figma !!! GitHub Figma Our open-source pixelated emoji pack was designed to communicate context about a story's content on HackerNoon and you can be amongst the first to try them! But before we tell you what you’ll get from this package, here’s a little refresher ⬇️ What are Emoji Credibility Indicators on HackerNoon Stories? Emoji Credibility Indicators provide essential context to the content within every HackerNoon story. Below the author’s profile on the story page, the “Credibility” section appears with a corresponding custom emoji and tooltip to indicate relevant information about the story to the reader. In the example above, you can see that David’s story contains two emoji credibility indicators: HODL, which indicates mentions of one or more cryptos that the author holds, and Associated Companies, which is used when the writer has or had any sort of business relationship with companies mentioned in the story. Learn more about Emoji Credibility Indicators here. Learn more about Emoji Credibility Indicators here . here Types of Emoji Credibility Indicators We have around 20 emoji credibility indicators for Context and Disclaimers, and Content Types, each with an attributed meaning and instructions on how to use them. So if you have a technological project, and want amazing pixelated emojis to represent/communicate credibility, this repo is for you! Read about all our emoji credibility indicators, what they mean, and how to use them here. Read about all our emoji credibility indicators, what they mean, and how to use them here . here Why Adding Context to Content Matters to the Future of Digital Text When lost in a good read, it may feel like there are only words, but the reality is, no text exists in a vacuum. All text has a setting. Too often on social media and the current internet, what surrounds the text is vanity metrics designed to keep you in the newsfeed, designed to re-affirm that what you’re doing is liked/upvoted/not-a-waste-of-time, instead of being designed to provide you with structured indications that define the context of the story. Read our help page fo more context about our emoji credibility indicators. Read our help page fo more context about our emoji credibility indicators. Read our help page fo more context about our emoji credibility indicators. What will you get from this open-source package? What will you get from this open-source package? Pixelated Emojis, designed on a 24px grid. Well crafted SVGs Fully customizable Ready-to-use for development via GitHub Repo and Figma! Pixelated Emojis, designed on a 24px grid. Well crafted SVGs Fully customizable Ready-to-use for development via GitHub Repo and Figma ! GitHub Repo Figma Sounds good? Try them out today and tell us about your experience here. Try them out today and tell us about your experience here . here Designing HackerNoon's Emoji Credibility Indicators: Get the developer’s perspective here. Designing HackerNoon's Emoji Credibility Indicators : Get the developer’s perspective here . Designing HackerNoon's Emoji Credibility Indicators here

HackerNoon's Emoji Credibility Indicators are Live on GitHub and Figma!

HackerNoon এর ইমোজি বিশ্বাসযোগ্যতা সূচকগুলি GitHub এবং Figma-এ লাইভ!

Die Emoji-Glaubwürdigkeitsindikatoren von HackerNoon sind live auf GitHub und Figma!

¡Los indicadores de credibilidad Emoji de HackerNoon están disponibles en GitHub y Figma!

Les indicateurs de crédibilité Emoji de HackerNoon sont en direct sur GitHub et Figma !

हैकरनून के इमोजी विश्वसनीयता संकेतक गिटहब और फिग्मा पर लाइव हैं!

HackerNoon の絵文字信頼性インジケーターが GitHub と Figma で公開されました。

HackerNoon의 이모티콘 신뢰성 지표가 GitHub 및 Figma에 게시되었습니다!

Os indicadores de credibilidade de Emoji do HackerNoon estão disponíveis no GitHub e no Figma!

Индикаторы достоверности Emoji от HackerNoon доступны на GitHub и Figma!

HackerNoon'un Emoji Güvenilirlik Göstergeleri GitHub ve Figma'da Yayında!

Các chỉ số đáng tin cậy về biểu tượng cảm xúc của HackerNoon hiện có trên GitHub và Figma!

HackerNoon 的 Emoji 可信度指标已在 GitHub 和 Figma 上线！

Rosetta Stone and machine-interpretability: Wikidata and a modeling paradigm 

In the Angular CDK there are a lot of cool, exciting, and helpful features. And the Overlay Module is one of the most powerful. It’s used to create things like dialogs, tooltips, menus, custom dropdowns, and more. I’ve already created a couple of posts on the Overlay Module, , and . If you’re unfamiliar with these concepts and haven’t read them, you should do that before reading this one because we will build off the examples that we created in them. Here, we’ll be focused on how we want an overlay to react when scrolling the container it’s positioned within. one where I cover the basics of setting them up another where I demonstrate different ways that they can be positioned within the viewport The overlay module provides us with four scrolling behaviors out of the box: Reposition Block Close Noop In this post, we’ll take a close look at each one. Let’s get to it! https://youtu.be/UtptUw0XpcQ?embedable=true Why We Need to Handle Scrolling When Using the CDK Connected Overlay One of the core concepts that we learned about in the Overlay basics post is that the physical markup for the overlay is injected at the end of the document just before the closing body tag. And this is what makes it so useful. This means that it can always be placed above any other content and is not constrained in any way by the containers that wrap the origin element. But, the fact that it is detached from the thing that we are positioning it in relation to, is problematic in some ways. Handling scroll is one of those problematic scenarios. If the markup was injected near the origin element, then we wouldn’t need to do anything on scroll, it would just scroll with the origin. But, there are lots of issues with that too which is why we need the overlay. Good news for us, we have several different options to handle scrolling. We can use any one of four, what are known as, Scroll Strategies provided in the Overlay module. We can even create a custom strategy if we want but that’s a topic for another post. Using the CDK Overlay Reposition Scroll Strategy The first strategy we’ll be looking at will be the repositioning strategy. With this position strategy, the popup gets repositioned as its parent scrolling container is scrolled. It makes it appear as if its markup is physically placed near its origin in the DOM. Ok, so here’s the demo project that we’ve been working on the last few posts with the Overlay module. We have a list of notable NBA players, and they each have a button that triggers a popup that we created using the directive. Now, before we can configure a position strategy for this pop-up, we need to first inject the Overlay service within our constructor. cdkConnectedOverlay player.component.ts import { ..., Overlay } from '@angular/cdk/overlay';
...
export class PlayerComponent {
    ...
    constructor(private overlay: Overlay) {}
} Now, we can create a property called . We’ll set this property to a provided scroll strategy from the Overlay service and then we’ll use it via an input on our in the template. To set this to a scroll strategy, we need to add access from the Overlay service and then we can use the strategy function. scrollStrategy cdkConnectedOverlay scrollStrategies reposition() export class PlayerComponent {
    ...
    protected scrollStrategy = this.overlay.scrollStrategies.reposition();
    ...
} And now, we can pass it to the directive in the template. To do this we use the input. And we simply pass it our property. cdkConnectedOverlayScrollStrategy scrollStrategy player.component.html <ng-template
    cdkConnectedOverlay
    ...
    [cdkConnectedOverlayScrollStrategy]="scrollStrategy">
    ...
</ng-template> Now, when we open up a pop-up, and then as we scroll, we can see that it scrolls along with the origin. Pretty crazy because the overlay has to recalculate its positioning while scrolling. But it’s surprisingly performant. Now, the repositioning strategy is the default behavior for this directive, so if this is what we want, we don’t need to pass a strategy to the directive at all. So just keep that in mind. Using the CDK Overlay Block Scroll Strategy Ok, next up we’re going to look at the “block” strategy. This strategy will prevent us from scrolling the container while the popup is open. So, now that we have everything set up, to change to another strategy is simple. We just need to switch from the method to the method instead. reposition() block() export class PlayerComponent {
    ...
    protected scrollStrategy = this.overlay.scrollStrategies.block();
    ...
} Now when we open the popup and try to scroll, nothing happens. So that’s another option, next up we’ll look at the “close” strategy. Using the CDK Overlay Close Scroll Strategy This one is pretty self-explanatory, but just in case it’s not clear, this strategy will close the overlay when scrolling. To use it, we simply need to replace the method with the method instead. block() close() export class PlayerComponent {
    ...
    protected scrollStrategy = this.overlay.scrollStrategies.close();
    ...
} There, now when we scroll the pop-up is closed. Using the CDK Overlay Noop Scroll Strategy Last up we have the noop strategy. This strategy just doesn’t do anything when we scroll. It doesn’t reposition, block, or close. Instead, it does nothing. Once again, let’s replace the close method with noop this time. export class PlayerComponent {
    ...
    protected scrollStrategy = this.overlay.scrollStrategies.noop();
    ...
} There, now as we scroll, we can see nothing happens. Ok, so there are all of the built-in scroll strategies but there’s one more important aspect when it comes to connected overlays and scrolling. It has to do with the scrolling container itself. How to Handle Overlay Scroll Strategies With Many Scrolling Containers Using the cdkScrollable directive Right now, our scrolling container is our root element, the HTML element. global_styles.scss html {
    ...
    overflow-y: auto;
    overflow-x: hidden;
} If we were to move the overflow styles off of the HTML element to an element within our app component instead. app.component.scss section {
    ...
    overflow-y: auto;
    overflow-x: hidden;
} And then, if we switch back to use the reposition scroll strategy. player.component.ts export class PlayerComponent {
    ...
    protected scrollStrategy = this.overlay.scrollStrategies.reposition();
    ...
} When we open our pop-up and scroll, we can see that the pop-up is no longer repositioning to keep itself attached to the origin. It’s almost like we’re using the noop strategy that we just learned about, but we’re not. This is because we need to let the overlay know that our scrolling container is actually a different element now. By default, if we don’t explicitly specify the scrolling container, it will fall back to the root element. In many cases this won’t work. More good news though, this is pretty easy to do. We need to first import the class in the component where our new scrolling container lives. In this example, it’s within our app component. CdkScrollable main.ts @Component({
    selector: 'app-root',
    imports: [..., CdkScrollable],
    ...
}) Now in the template we can add the directive on the scrolling container itself which is the section element. cdkScrollable app.component.html <section cdkScrollable>
    ...
</section> And now, the overlay will use this for its scrolling context. So, when we open it up again and scroll, it’s correctly getting repositioned again. Alright, so you now have several different ways to handle pop-ups and scrolling. Stay tuned for more posts on the Overlay module in the future! Found This Helpful? If you found this article helpful and want to show some love, you can always buy me a coffee! Want to See It in Action? Check out the demo code and examples of these techniques in the stackblitz example below. If you have any questions or thoughts, don’t hesitate to leave a comment. https://stackblitz.com/edit/stackblitz-starters-wpjhcn?ctl=1&embed=1&file=src%2Fplayer%2Fplayer.component.ts&embedable=true Also published . here

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